last-train
==========

last-train finds the rates (probabilities) of insertion, deletion, and
substitutions between two sets of sequences.  It thereby finds
suitable substitution and gap scores for aligning them.

It (probabilistically) aligns the sequences using some initial score
parameters, then estimates better score parameters based on the
alignments, and repeats this procedure until the parameters stop
changing.

The usage is like this::

  lastdb mydb reference.fasta
  last-train mydb queries.fasta

last-train prints a summary of each alignment step, followed by the
final score parameters, in a format that can be read by `lastal's -p
option <lastal.html#score-options>`_.

last-train can read .gz files, or from pipes::

  bzcat queries.fasta.bz2 | last-train mydb

Options
-------

  -h, --help
         Show a help message, with default option values, and exit.
  -v, --verbose
         Show more details of intermediate steps.

Training options
~~~~~~~~~~~~~~~~

  --revsym
         Force the substitution scores to have reverse-complement
         symmetry, e.g. score(A→G) = score(T→C).  This is often
         appropriate, if neither strand is "special".
  --matsym
         Force the substitution scores to have directional symmetry,
         e.g. score(A→G) = score(G→A).
  --gapsym
         Force the insertion costs to equal the deletion costs.
  --pid=PID
         Ignore alignments with > PID% identity.  This aims to
         optimize the parameters for low-similarity alignments
         (similarly to the BLOSUM matrices).
  --postmask=NUMBER
         By default, last-train ignores alignments of mostly-lowercase
         sequence (by using `last-postmask <last-postmask.html>`_).
         To turn this off, do ``--postmask=0``.
  --sample-number=N
         Use N randomly-chosen chunks of the query sequences.  The
         queries are chopped into fixed-length chunks (as if they were
         first concatenated into one long sequence).  If there are ≤ N
         chunks, all are picked.  Otherwise, if the final chunk is
         shorter, it is never picked.  0 means use everything.
  --sample-length=L
         Use randomly-chosen chunks of length L.

All options below this point are passed to lastal to do the
alignments: they are described in more detail at `<lastal.html>`_.

Initial parameter options
~~~~~~~~~~~~~~~~~~~~~~~~~

  -r SCORE   Initial match score.
  -q COST    Initial mismatch cost.
  -p NAME    Initial match/mismatch score matrix.
  -a COST    Initial gap existence cost.
  -b COST    Initial gap extension cost.
  -A COST    Initial insertion existence cost.
  -B COST    Initial insertion extension cost.

Alignment options
~~~~~~~~~~~~~~~~~

  -D LENGTH  Query letters per random alignment.  (See `here
             <last-evalues.html>`_.)
  -E EG2     Maximum expected alignments per square giga.  (See `here
             <last-evalues.html>`_.)
  -s NUMBER  Which query strand to use: 0=reverse, 1=forward, 2=both.
             If specified, this parameter is written in last-train's
             output, so it will override lastal's default.
  -S NUMBER  Specify how to use the substitution score matrix for
             reverse strands.  If you use ``--revsym``, this makes no
             difference.  "0" means that the matrix is used as-is for
             all alignments.  "1" (the default) means that the matrix
             is used as-is for alignments of query sequence forward
             strands, and the complemented matrix is used for query
             sequence reverse strands.

             This parameter is always written in last-train's output,
             so it will override lastal's default.

  -C COUNT   Before extending gapped alignments, discard any gapless
             alignment whose query range lies in COUNT other gapless
             alignments with higher score-per-length.  This aims to
             reduce run time.
  -T NUMBER  Type of alignment: 0=local, 1=overlap.
  -m COUNT   Maximum number of initial matches per query position.
  -k STEP    Look for initial matches starting only at every STEP-th
             position in each query.
  -P COUNT   Number of parallel threads.
  -X NUMBER  How to score a match/mismatch involving N (for DNA) or X
             (otherwise).  By default, the lowest match/mismatch score
             is used. 0 means the default; 1 means treat reference
             Ns/Xs as fully-ambiguous letters; 2 means treat query
             Ns/Xs as ambiguous; 3 means treat reference and query
             Ns/Xs as ambiguous.

             If specified, this parameter is written in last-train's
             output, so it will override lastal's default.

  -Q NUMBER  How to read the query sequences.  By default, they must
             be in ``fasta`` format.  ``-Q0`` means ``fasta`` or
             ``fastq-ignore``.  ``-Q1`` means ``fastq-sanger``.

             The ``fastq`` formats are described here:
             `<lastal.html>`_.  ``fastq-ignore`` means that the
             quality data is ignored, so the results will be the same
             as for ``fasta``.

             For ``fastq-sanger``, last-train assumes the quality
             codes indicate substitution error probabilities, *not*
             insertion or deletion error probabilities.  If this
             assumption is dubious (e.g. for data with many insertion
             or deletion errors), it may be better to use
             ``fastq-ignore``.  For ``fastq-sanger``, last-train finds
             the rates of substitutions not explained by the quality
             data (ideally, real substitutions as opposed to errors).

             If specified, this parameter is written in last-train's
             output, so it will override lastal's default.

Details
-------

* last-train (and lastal) uses "Model A", in Figure 5A of btz576_.

* last-train (and lastal) converts between path and alignment
  parameters as in Supplementary Section 3.1 of btz576_.

* last-train converts probabilities to scores using an arbitrary scale
  factor.  (If all the scores are multiplied by any positive constant,
  it makes no difference to alignment.)  This scale is determined by
  the initial score parameters.

* last-train uses parameters with "homogeneous letter probabilities"
  and "balanced length probability" (btz576_).

* last-train rounds the scores to integers, which makes them slightly
  inaccurate.  It then finds an adjusted scale factor (without
  changing the scores), which makes the integer-rounded scores
  correspond to homogeneous letter probabilities and balanced length
  probability.  It writes this adjusted scale as a "-t" option for
  lastal, e.g. "-t4.4363".

* In rare cases, it may be impossible to find such an adjusted scale
  factor.  If that happens, last-train doubles the original scale (to
  reduce the inaccuracy of integer rounding), until the problem goes
  away.

.. _btz576: https://doi.org/10.1093/bioinformatics/btz576

Bugs
----

* last-train assumes that gap lengths roughly follow a geometric
  distribution.  If they do not (which is often the case), the results
  may be poor.

* last-train can fail for various reasons, e.g. if the sequences are
  too dissimilar.  If it fails to find any alignments, you could try
  `reducing the alignment significance threshold
  <last-tutorial.html#example-6-find-very-short-dna-alignments>`_ with
  option -D.

* last-train cannot handle DNA-versus-protein alignment.
